{"id":"W4407761346","doi":"10.1016/j.xcrp.2025.102438","title":"Intelligent wearable system design for personalized knee motion and swelling monitoring in osteoarthritis care","year":2025,"lang":"en","type":"article","venue":"Cell Reports Physical Science","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Hong Kong Polytechnic University","keywords":"Wearable computer; Osteoarthritis; Computer science; Motion capture; Swelling; Medicine; Motion (physics); Physical medicine and rehabilitation; Embedded system; Artificial intelligence; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002174766,0.0001023982,0.0001647917,0.00007227732,0.0001303854,0.00008057163,0.0000566644,0.00002669835,4.462383e-7],"category_scores_gemma":[0.0000542433,0.0001014315,0.00002552617,0.0002624676,0.00008547384,0.000168618,0.00002354404,0.00005473634,6.874676e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001572221,"about_ca_system_score_gemma":0.00002230987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002084904,"about_ca_topic_score_gemma":6.958167e-7,"domain_scores_codex":[0.9991457,0.00001178058,0.0001932204,0.0002729386,0.0001247993,0.0002515415],"domain_scores_gemma":[0.9996606,0.00006895015,0.00003403533,0.000125319,0.00005341125,0.00005769435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000007107607,0.00000993261,0.0002355263,0.000389091,0.000001501873,0.00002391897,0.0007297342,0.432525,0.5477034,0.0004213697,0.00000103536,0.01795241],"study_design_scores_gemma":[0.0001488508,0.00003251549,0.000213763,0.0004061218,0.000007923064,0.000008021642,0.0008838365,0.04414507,0.9533598,0.0004609982,0.0001894069,0.0001437362],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8721169,0.0006258751,0.1245193,0.000001529496,0.0006982271,0.0002434852,6.735646e-7,0.0001323193,0.001661628],"genre_scores_gemma":[0.9966282,0.00002106623,0.003115835,0.000001139285,0.00007134423,0.00004864893,6.800154e-7,0.000009887061,0.0001031584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4056564,"threshold_uncertainty_score":0.4136257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01498124129954433,"score_gpt":0.2451097641347098,"score_spread":0.2301285228351654,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}